Digital Twin-Enabled Monitoring of Mining Haul Trucks with Expert System Integration: A Case Study in an Experimental Open-Pit Mine

In the mining industry, the use of digital transformation has become increasingly important to improve the productivity, efficiency, and availability of machinery and equipment. The implementation of digital twin technology has shown great potential in tackling issues related to maintenance, production, and safety in the industry. This paper presents a case study on the development of a digital twin-enabled monitoring system for mining haul trucks with expert system integration. The system is designed to provide real-time tracking and monitoring of haul trucks, diagnose potential anomalies, and troubleshoot issues using a statistical process control algorithm. The proposed framework encapsulates five layers: physical layer, data acquisition layer, data management layer, applications layer, and decision support layer. The study presents the materials and methods used in implementing the digital twin framework and discusses the results obtained.